scholarly journals Cloud climatologies from the InfraRed Sounders AIRS and IASI: Strengths, Weaknesses and Applications

2017 ◽  
Author(s):  
Claudia J. Stubenrauch ◽  
Artem G. Feofilov ◽  
Sofia E. Protopapadaki ◽  
Raymond Armante
Keyword(s):  
Cloud Amount ◽  
Co2 Concentration ◽  
Boreal Summer ◽  
Cloud Base ◽  
Cloud Detection ◽  
Ancillary Data ◽  
Total Cloud Amount ◽  
Low Level ◽  
Cloud Properties ◽  
High Level

Abstract. The cloud retrieval scheme developed at the Laboratoire de Météorologie Dynamique (LMD) can now be easily adapted to any Infrared (IR) sounder: the CIRS (Clouds from IR Sounders) retrieval applies improved radiative transfer, as well as an original method accounting for atmospheric spectral transmissivity changes associated with CO2 concentration. The latter is essential when considering long-term time series of cloud properties. For the 13-year and 8-year global climatologies of cloud properties from observations of the Atmospheric IR Sounder (AIRS) and of the IR Atmospheric Interferometer (IASI), respectively, we used the latest ancillary data (atmospheric profiles, surface emissivities and atmospheric spectral transmissivities). The A-Train active instruments, lidar and radar of the CALIPSO and CloudSat missions, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height as well as to explore the vertical structure of different cloud types. CIRS cloud detection agreement with CALIPSO-CloudSat is about 84%–85% over ocean, 79%–82% over land and 70%–73% over ice / snow, depending on atmospheric ancillary data. Global cloud amount has been estimated to 67%–70%. CIRS cloud height coincides with the middle between the cloud top and the apparent cloud base (real base for optically thin clouds or height at which the cloud reaches opacity) independent of cloud emissivity, which is about 1 km below cloud top for low-level clouds and about 1.5 km to 2.5 km below cloud top for high-level clouds, slightly increasing because the apparent vertical cloud extent is slightly larger for large cloud emissivity. IR sounders are in particular advantageous for the retrieval of upper tropospheric cloud properties, with a reliable cirrus identification down to an IR optical depth of 0.1, day and night. Total cloud amount consists of about 40% high-level clouds and about 40% low-level clouds and 20% mid-level clouds, the latter two only detected when not hidden by upper clouds. Upper tropospheric clouds are most abundant in the tropics, where high opaque clouds make out 7.5%, thick cirrus 27.5% and thin cirrus about 21.5% of all clouds. The asymmetry in upper tropospheric cloud amount between Northern and Southern hemisphere with annual mean of 5% has a pronounced seasonal cycle with a maximum of 25% in boreal summer, which can be linked to the shift of the ITCZ peak latitude. Comparing tropical geographical change patterns of high opaque clouds with that of thin cirrus as a function of changing tropical mean surface temperature indicates that their response to climate change may be quite different, with potential consequences on the atmospheric circulation.

scholarly journals Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

2017 ◽  
Vol 17 (22) ◽  
pp. 13625-13644 ◽  
Author(s):  
Claudia J. Stubenrauch ◽  
Artem G. Feofilov ◽  
Sofia E. Protopapadaki ◽  
Raymond Armante
Keyword(s):  
Surface Temperature ◽  
Cloud Amount ◽  
Co2 Concentration ◽  
Boreal Summer ◽  
Ancillary Data ◽  
Low Level ◽  
Geographical Patterns ◽  
Cloud Properties ◽  
The Mean ◽  
High Level

Abstract. Global cloud climatologies have been built from 13 years of Atmospheric Infrared Sounder (AIRS) and 8 years of Infrared Atmospheric Sounding Interferometer (IASI) observations, using an updated Clouds from Infrared Sounders (CIRS) retrieval. The CIRS software can handle any infrared (IR) sounder data. Compared to the original retrieval, it uses improved radiative transfer modelling, accounts for atmospheric spectral transmissivity changes associated with CO2 concentration and incorporates the latest ancillary data (atmospheric profiles, surface temperature and emissivities). The global cloud amount is estimated to be 0.67–0.70, for clouds with IR optical depth larger than about 0.1. The spread of 0.03 is associated with ancillary data. Cloud amount is partitioned into about 40 % high-level clouds, 40 % low-level clouds and 20 % mid-level clouds. The latter two categories are only detected in the absence of upper clouds. The A-Train active instruments, lidar and radar of the CALIPSO and CloudSat missions, provide a unique opportunity to evaluate the retrieved AIRS cloud properties. CIRS cloud height can be approximated either by the mean layer height (for optically thin clouds) or by the mean between cloud top and the height at which the cloud reaches opacity. This is valid for high-level as well as for low-level clouds identified by CIRS. IR sounders are particularly advantageous to retrieve upper-tropospheric cloud properties, with a reliable cirrus identification, day and night. These clouds are most abundant in the tropics, where high opaque clouds make up 7.5 %, thick cirrus 27.5 % and thin cirrus about 21.5 % of all clouds. The 5 % annual mean excess in high-level cloud amount in the Northern compared to the Southern Hemisphere has a pronounced seasonal cycle with a maximum of 25 % in boreal summer, in accordance with the moving of the ITCZ peak latitude, with annual mean of 4° N, to a maximum of 12° N. This suggests that this excess is mainly determined by the position of the ITCZ. Considering interannual variability, tropical cirrus are more frequent relative to all clouds when the global (or tropical) mean surface gets warmer. Changes in relative amount of tropical high opaque and thin cirrus with respect to mean surface temperature show different geographical patterns, suggesting that their response to climate change might differ.

scholarly journals Seasonal cycle of cloud cover analyzed using Meteosat images

1998 ◽  
Vol 16 (3) ◽  
pp. 331-341 ◽  
Author(s):  
J. Massons ◽  
D. Domingo ◽  
J. Lorente
Keyword(s):  
Spatial Resolution ◽  
Seasonal Cycle ◽  
Cloud Cover ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Total Cloud Amount ◽  
Cloud Parameters ◽  
Cloud Properties

Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat

International Satellite Cloud Climatology Project: Extending the Record

2021 ◽  
pp. 1-62
Author(s):  
William B. Rossow ◽  
Kenneth R. Knapp ◽  
Alisa H Young
Keyword(s):  
Product Design ◽  
Cloud Amount ◽  
Cloud Microphysics ◽  
Temperature Threshold ◽  
Ancillary Data ◽  
Total Cloud Amount ◽  
High Cloud ◽  
Enso Events ◽  
Cloud Properties ◽  
Low Cloud

AbstractISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1°?grid, all other gridded products at 1.0°-equivalent equal-area, separate-satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data), expanded documentation, the processing code and an Operations Guide are available online. Notable changes are: (1) a lowered ice-liquid temperature threshold, (2) a treatment of the radiative effects of aerosols and surface temperature inversions, (3) refined specification of the assumed cloud microphysics, and (4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events.

scholarly journals Evaluation of a Statistical Model of Cloud Vertical Structure Using Combined CloudSat and CALIPSO Cloud Layer Profiles

2010 ◽  
Vol 23 (24) ◽  
pp. 6641-6653 ◽  
Author(s):  
William B. Rossow ◽  
Yuanchong Zhang
Keyword(s):  
Statistical Model ◽  
Vertical Structure ◽  
Spatial Scales ◽  
Three Dimensional ◽  
Cloud Amount ◽  
Cloud Layer ◽  
Middle Level ◽  
Polar Regions ◽  
Total Cloud Amount ◽  
Low Level

Abstract A model of the three-dimensional distribution of clouds was developed from the statistics of cloud layer occurrence from the International Satellite Cloud Climatology Project (ISCCP) and the statistics of cloud vertical structure (CVS) from an analysis of radiosonde humidity profiles. The CVS model associates each cloud type, defined by cloud-top pressure of the topmost cloud layer and total column optical thickness, with a particular CVS. The advent of satellite cloud radar (CloudSat) and lidar [Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements (together C&C) of CVS allows for a quantitative evaluation of this statistical model. The zonal monthly-mean cloud layer distribution from the ISCCP CVS agrees with that from C&C to within 10% (when normalized to the same total cloud amount). The largest differences are an overestimate of middle-level cloudiness in winter polar regions, an overestimate of cloud-top pressures of the highest-level clouds, especially in the tropics, and an underestimate of low-level cloud amounts over southern midlatitude oceans. A more severe test of the hypothesized relationship is made by comparing CVS for individual satellite pixels. The agreement of CVS is good for isolated low-level clouds and reasonably good when the uppermost cloud layer is a high-level cloud; however, the agreement is not good when the uppermost cloud layer is a middle-level cloud, even when ISCCP correctly locates cloud top. An improved CVS model combining C&C and ISCCP may require classification at spatial scales larger than individual satellite pixels.

scholarly journals Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

2017 ◽  
Vol 17 (9) ◽  
pp. 5789-5807 ◽  
Author(s):  
John C. Kealy ◽  
Franco Marenco ◽  
John H. Marsham ◽  
Luis Garcia-Carreras ◽  
Pete N. Francis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Second Generation ◽  
High Surface ◽  
Cloud Amount ◽  
Limiting Factors ◽  
Cloud Detection ◽  
Airborne Remote Sensing ◽  
Horizontal Extent ◽  
Cloud Properties ◽  
Cloud Mask

Abstract. Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km  ×  3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

scholarly journals The effect of low-level thin arctic clouds on shortwave irradiance: evaluation of estimates from spaceborne passive imagery with aircraft observations

2021 ◽  
Vol 14 (4) ◽  
pp. 2673-2697
Author(s):  
Hong Chen ◽  
Sebastian Schmidt ◽  
Michael D. King ◽  
Galina Wind ◽  
Anthony Bucholtz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Surface Albedo ◽  
The Arctic ◽  
Cloud Detection ◽  
Radiative Effects ◽  
Study Region ◽  
Airborne Measurements ◽  
Low Level ◽  
Cloud Properties

Abstract. Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.

scholarly journals Low Level Cloud and Dynamical Features within the Southern West African Monsoon

2018 ◽  
Author(s):  
Cheikh Dione ◽  
Fabienne Lohou ◽  
Marie Lothon ◽  
Bianca Adler ◽  
Karmen Babić ◽  
...  
Keyword(s):  
West Africa ◽  
Onset Time ◽  
Boreal Summer ◽  
Cloud Base ◽  
Time Range ◽  
Low Level ◽  
Stratus Clouds ◽  
Monsoon Flow ◽  
Low Level Jet ◽  
Core Height

Abstract. During the Boreal summer, the monsoon season that takes place in West Africa is accompanied by low stratus clouds over land, that stretch from the Guinean coast several hundred kilometers inland. These clouds form during the night and dissipate during the following day. Inherently linked with the diurnal cycle of monsoon flow, those clouds still remain poorly documented and understood.Moreover, numerical climate and weather models lack fine quantitative documentation of cloud macrophysical characteristics and the dynamical and thermodynamical structures occupying the lowest troposphere. The Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) field experiment, which took place in summer 2016, addresses this knowledge gap. Low level atmospheric dynamics and low-level cloud macrophysical properties are analyzed using in-situ and remote sensing continuous measurements collected from 20 June to 30 July at Savè, Benin, roughly 180 km from the coast. The macrophysical characteristics of the stratus clouds are deduced from a ceilometer, an infrared cloud camera and cloud radar. Onset times, evolution, dissipation times, base heights and thickness are evaluated. The Data from a UHF (Ultra High Frequency) wind profiler, a microwave radiometer and an energy balance station are used to quantify the occurrence and characteristics of the monsoon flow, the nocturnal low-level jet and the cold air mass inflow propagating northwards from the coast of the Gulf of Guinea. The results show that these dynamical structures are very regularly observed during the entire 41-day documented period. Monsoon flow is observed 100 % of the time. The so-called maritime inflow and the nocturnal low level jet are also systematic features in this area. According to monsoon flow conditions, the maritime inflow reaches Savè around 18:00–19:00 UTC on average: this timing is correlated with the strength of the monsoon flow. This time of arrival is close to the time range of the nocturnal low level jet settlement. As a result, these phenomena are difficult to distinguish at the Savè site. The low level jet occurs every night, except during rain events, and is associated 65 % of the time with low stratus clouds. Stratus cloud form between 22:00 UTC and 06:00 UTC at an elevation close to the nocturnal low level jet core height. The cloud base height, 310 ± 30 m above ground level (a.g.l.) is rather stationary during the night and remains below the jet core height. The cloud top height, at 640 ± 100 m a.g.l., is typically found above the jet core. The nocturnal low level jet, low level clouds, monsoon flow and maritime inflow reveal significant day-to-day variability during the summer. Distributions of strength, depth, onset time, break up time, etc. are quantified here.

scholarly journals Clouds over the summertime Sahara: An evaluation of Met Office Meteosat retrievals using airborne remote sensing

2016 ◽  
Author(s):  
John C. Kealy ◽  
Franco Marenco ◽  
John H. Marsham ◽  
Luis Garcia-Carreras ◽  
Pete N. Francis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mineral Dust ◽  
Cloud Amount ◽  
Limiting Factors ◽  
Cloud Detection ◽  
Airborne Remote Sensing ◽  
Horizontal Extent ◽  
Cloud Properties ◽  
Infrared Imager ◽  
Cloud Mask

Abstract. Novel methods of cloud detection are applied to the unique Fennec aircraft dataset, to evaluate the Met Office derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board Meteosat. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height, and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent which is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust.

scholarly journals SegCloud: a novel cloud image segmentation model using deep Convolutional Neural Network for ground-based all-sky-view camera observation

2019 ◽  
Author(s):  
Wanyi Xie ◽  
Dong Liu ◽  
Ming Yang ◽  
Shaoqing Chen ◽  
Benge Wang ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Cloud Cover ◽  
Weather Forecast ◽  
Cloud Detection ◽  
Feature Maps ◽  
Deep Convolutional Neural Networks ◽  
Softmax Classifier ◽  
Discrimination Ability ◽  
Low Level ◽  
High Level

Abstract. Cloud detection and cloud properties have significant applications in weather forecast, signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the fundamental and important step to derive cloud cover. However, traditional segmentation methods rely on low-level visual features of clouds, and often fail to achieve satisfactory performance. Deep Convolutional Neural Networks (CNNs) are able to extract high-level feature information of object and have become the dominant methods in many image segmentation fields. Inspired by that, a novel deep CNN model named SegCloud is proposed and applied to accurate cloud segmentation based on ground-based observation. Architecturally, SegCloud possesses symmetric encoder-decoder structure. The encoder network combines low-level cloud features to form high-level cloud feature maps with low resolution, and the decoder network restores the obtained high-level cloud feature maps to the same resolution of input images. The softmax classifier finally achieves pixel-wise classification and outputs segmentation results. SegCloud has powerful cloud discrimination ability and can automatically segment the whole sky images obtained by a ground-based all-sky-view camera. Furthermore, a new database, which includes 400 whole sky images and manual-marked labels, is built to train and test the SegCloud model. The performance of SegCloud is validated by extensive experiments, which show that SegCloud is effective and accurate for ground-based cloud segmentation and achieves better results than traditional methods. Moreover, the accuracy and practicability of SegCloud is further proved by applying it to cloud cover estimation.

scholarly journals Shortwave Radiative Effect of Arctic Low-Level Clouds: Evaluation of Imagery-Derived Irradiance with Aircraft Observations

2019 ◽  
Author(s):  
Hong Chen ◽  
Sebastian Schmidt ◽  
Michael D. King ◽  
Galina Wind ◽  
Anthony Bucholtz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Surface Albedo ◽  
Detection Threshold ◽  
The Arctic ◽  
Radiative Effect ◽  
Cloud Detection ◽  
Study Region ◽  
Low Level ◽  
Cloud Properties

Abstract. Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from space-borne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This entails the derivation of surface albedo from SSFR/BBR and camera imagery for heterogeneous surfaces in the marginal ice zone (MIZ), as well as subsequent measurement-model inter-comparisons in the presence of thin clouds. In addition to MODIS cloud retrievals and surface albedo from SSFR, we used temperature and humidity data from in-situ data and reanalysis (MERRA-2). The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based measurements, and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case studies, about 22 % of clouds remained undetected (cloud optical thickness less than 0.5). The radiative effect of clouds above the detection threshold was −40 W m−2 above cloud, and −39 W m−2 below the cloud layer, and the optical thickness from the MODIS "1621" cloud product was consistent with the reflected and transmitted irradiance observations. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach, that would make it more dependable in the Arctic. Regardless of the cloud retrieval method, there is a need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effect from space-borne remote sensing.

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